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First, congratulations on how good DynamicalSystems is becoming. This work in Julia is amazing.
In nlts.jl the extension of reconstruction to Broomhead and King is really convincing and fast.
Since the pratitioner's starting point is always a dataset, it would be good to determine if the three times series from a given synthetic dataset (in your example gissinger + noise) come from either the same model or from three different models. At present, you apply separate SSA to each time series and then determine that tau=30 in each case. Can you extend SSA to Multichannel SSA https://arxiv.org/pdf/1309.5050 to complete the demonstration and bring to Julia a diagnostic tool already available in R.
The implementation you are suggesting seems straight forward, and a very nice addition, there is no doubt there! It does seem like a significant amount of work, but definitely not the difficult kind.
Unfortunately at the moment I am super-busy, so I cannot promise that I can get around to do it.
But since it seems a not very difficult one, perhaps you want to tackle it doing a Pull Request? I can promise that I will review the code and help as much as I can.
From @finmod on January 30, 2018 12:59
First, congratulations on how good DynamicalSystems is becoming. This work in Julia is amazing.
In nlts.jl the extension of reconstruction to Broomhead and King is really convincing and fast.
Since the pratitioner's starting point is always a dataset, it would be good to determine if the three times series from a given synthetic dataset (in your example gissinger + noise) come from either the same model or from three different models. At present, you apply separate SSA to each time series and then determine that tau=30 in each case. Can you extend SSA to Multichannel SSA https://arxiv.org/pdf/1309.5050 to complete the demonstration and bring to Julia a diagnostic tool already available in R.
Copied from original issue: JuliaDynamics/DynamicalSystems.jl#60
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